Language measures correlate with other measures used to study emotion

Area of Science:

• Psychology
• Linguistics
• Affective Science

Background:

• Language analysis is increasingly used to study emotion.
• Previous research primarily focused on language and self-report correlations.
• The relationship between language and other emotion measures remains less understood.

Purpose of the Study:

• To investigate the associations between language measures and a wider array of emotion indicators.
• To examine these associations across various established linguistic dictionaries.
• To determine the consistency of these relationships in multimodal datasets.

Main Methods:

• Analysis of three large, multimodal datasets with varying participant numbers and text lengths.
• Testing associations between language-derived emotion (valence and discrete emotions) and self-report, observer report, facial cues, and vocal cues.
• Comparison of results across multiple dictionaries (LIWC-22, NRC, Lexical Suite, ANEW, VADER).

Main Results:

• Language measures consistently correlated with observer and self-report measures across datasets.
• Significant associations were found between language measures of valence and facial cues, but not discrete emotions.
• Language measures did not consistently associate with vocal cues.
• Dictionary choice did not significantly impact the observed associations.

Conclusions:

• Language measures, especially those indicating valence, show robust correlations with multiple other emotion assessment methods.
• Language analysis offers a viable and practical approach for emotion research, particularly when other data modalities are limited.
• Researchers can confidently employ language analysis to study emotion, complementing or substituting traditional methods.